Section: New Results

Throughput optimization for pipeline workflow scheduling with setup times

We tackle [15] pipeline workflow applications that are executed on a distributed platform with setup times. In such applications, several computation stages are interconnected as a linear application graph, and each stage holds a buffer of limited size where intermediate results are stored and a processor setup time occurs when passing from one stage to another. The considered stage/processor mapping strategy is based on interval mappings, where an interval of consecutive stages is performed by the same processor and the objective is the throughput optimization. Typical examples for this kind of applications are streaming applications such as audio and video coding or decoding, image processing using co-processing devices as FPGA. Even when neglecting setup times, the problem is NP-hard on heterogeneous platforms and we therefore restrict to homogeneous resources. We provide an optimal algorithm for constellations with identical buffer capacities. When buffer sizes are not fixed, we deal with the problem of allocating the buffers in shared memory and present a $b/(b+1)$-approximation algorithm.